Search Results (31)

Ting, Tai, Lou, and Ge are types of ancient buildings that represent traditional Chinese architecture and culture. They are primarily constructed using mortise and tenon joints, complemented by brick and stone foundations, showcasing traditional architectural craftsmanship. However, research aimed at conserving, inheriting, and rejuvenating these buildings is limited, despite their status as Provincial Cultural Relic Protection Units of China. Therefore, the aim of this study was to reveal the spatial distribution of Ting, Tai, Lou, and Ge buildings across China, as well as the factors driving differences in their spatial distribution. Tourist experiences and building popularity were also explored. The spatial analysis method (e.g., Standard deviation ellipse and Geographic detector), Word cloud generation, and sentiment analysis, which uses Natural Language Processing techniques to identify subjective emotions in text, were applied to investigated the research issues. The key findings of this study are as follows. The ratio of Ting, Tai, Lou, and Ge buildings in Southeast China to that in Northwest China divided by the “Heihe–Tengchong” Line, an important demographic boundary in China with the ratio of permanent residents in the two areas remaining stable at 94:6, was 94.6:5.4. Geographic detector analysis revealed that six of the seven natural and socioeconomic factors (topography, waterways, roads, railways, population, and carbon dioxide emissions) had a significant influence on the spatial heterogeneity of these cultural heritage buildings in China, with socioeconomic factors, particularly population, having a greater influence on building spatial distributions. All seven factors (including the normalized difference vegetation index, an indicator used to assess vegetation health and coverage) were significant in Southeast China, whereas all factors were non-significant in Northwest China, which may be explained by the small number of buildings in the latter region. The average rating scores and heat scores for Ting, Tai, Lou, and Ge buildings were 4.35 (out of 5) and 3 (out of 10), respectively, reflecting an imbalance between service quality and popularity. According to the percentages of positive and negative reviews, Lou buildings have much better tourism services than other buildings, indicating a need to improve services to attract more tourists to Ting, Tai, and Ge buildings. Four main types of words were used with high frequency in the tourism reviews collected form Ctrip, a popular online travel platform in China: (1) historical stories; (2) tourism; (3) culture; and (4) cities/provinces. Ting and Tai buildings showed similar word clouds, as did Lou and Ge buildings, with only the former including historical stories. Conversely, landmark was a high-frequency word only in the reviews of Lou and Ge buildings. Specific suggestions were proposed based on the above findings to promote tourism and revive ancient Chinese architecture. Full article

Background/Objectives: Rock climbing is becoming more popular, leading to an increased focus on diagnosing and treating related injuries. Finger pulley and flexor tendon injuries are common among climbers, with the A2 pulley being the most frequently affected. High-resolution ultrasound (US) is the preferred method for detecting pulley injuries. This study aimed to determine the reliability and validity of US in identifying anatomical landmarks for diagnosing A2 pulley ruptures. Methods: This study was cross-sectional, involving 36 fingers from 4 cadaver arms. A Canon Aplio i800 US machine was used to measure two anatomical landmarks: the midpoint of the proximal phalanx and the distal edge of the A2 pulley. For the first anatomical landmark, the length of the proximal phalanx (PP distance), and for the second landmark, the distance between the distal edges of the proximal phalanx and the A2 pulley (“A” distance), were measured. Measurements were performed by two sonographers and compared to a digital caliper measurement taken post-cadaver dissection. Observers were blinded during measurements to ensure unbiased results. Results: Overall PP distance measured by US (O1: 37.5 ± 5.3 mm, O2: 37.8 ± 5.4 mm) tended to be shorter than caliper measurements (O3: 39.5 ± 5.5 mm). The differences between sonographers were minimal, but larger when compared to caliper measurements. High reliability for PP distance measurement was observed, especially between sonographers, with an ICC average of 0.99 (0.98, 1.00). However, reliability was lower for the “A” distance, with significant differences between US and caliper measurements. Regarding validity, US measurements were valid when compared to caliper measurements for PP distance, but not as reliable for the “A” due to wider confidence intervals. While US can substitute caliper measurements for PP distance (LR, Y:O2, X:O3, −0.70 (−3.28–1.38), 0.98 (0.93 ± 1.04)), its validity for “A” distance is lower (LR, Y:O2, X:O3, −2.37 (−13.53–4.83), 1.02 (0.62–1.75)). Conclusions: US is a reliable and valid tool in identifying anatomical landmarks for diagnosing A2 pulley ruptures, particularly for detecting the midpoint of the proximal phalanx. This is important to differentiate between complete and partial A2 pulley tears. However, the measurement of the “A” distance requires further refinement. These findings support efforts to standardize US examination protocols and promote consensus in diagnostic methodology, though further research is needed to address the remaining challenges. Full article

Background/Objectives: We sought to improve accuracy while minimizing radiation hazards, improving surgical outcomes, and preventing potential complications. Despite the increasing popularity of these systems, a limited number of papers have been published addressing the historical evolution, detailing the areas of use, and discussing the advantages and disadvantages, of this increasingly popular system in lumbar spine surgery. Our objective was to offer readers a concise overview of navigation system history in lumbar spine surgeries, the techniques involved, the advantages and disadvantages, and suggestions for future enhancements to the system. Methods: A comprehensive review of the literature was conducted, focusing on the development and implementation of navigation systems in lumbar spine surgeries. Our sources include PubMed-indexed peer-reviewed journals, clinical trial data, and case studies involving technologies such as computer-assisted surgery (CAS), image-guided surgery (IGS), and robotic-assisted systems. Results: To develop more practical, effective, and accurate navigation techniques for spine surgery, consistent advancements have been made over the past four decades. This technological progress began in the late 20th century and has since encompassed image-guided surgery, intraoperative imaging, advanced navigation combined with robotic assistance, and artificial intelligence. These technological advancements have significantly improved the accuracy of implant placement, reducing the risk of misplacement and related complications. Navigation has also been found to be particularly useful in tumor resection and minimally invasive surgery (MIS), where conventional anatomic landmarks are lacking or, in the case of MIS, not visible. Additionally, these innovations have led to shorter operative times, decreased radiation exposure for patients and surgical teams, and lower rates of reoperation. As navigation technology continues to evolve, future innovations are anticipated to further enhance the capabilities and accessibility of these systems, ultimately leading to improved patient outcomes in lumbar spine surgery. Conclusions: The initial limited utilization of navigation system in spine surgery has further expanded to encompass almost all fields of lumbar spine surgeries. As the cost-effectiveness and number of trained surgeons improve, a wider use of the system will be ensured so that the navigation system will be an indispensable tool in lumbar spine surgery. However, continued research and development, along with training programs for surgeons, are essential to fully realize the potential of these technologies in clinical practice. Full article

People’s perception of forensic evidence is greatly influenced by crime TV series. The analysis of the human voice is no exception. However, unlike fingerprints—with which fiction and popular beliefs draw an incorrect parallel—the human voice varies according to many factors, can be altered deliberately, and its potential uniqueness has yet to be proven. Starting with a cursory examination of landmarks in forensic voice analysis that exemplify how the voiceprint fallacy came about and why people think they can recognize people’s voices, we then provide a thorough inspection of over 100 excerpts from TV series. Through this analysis, we seek to characterize the narrative and aesthetic processes that fashion our perception of scientific evidence when it comes to identifying somebody based on voice analysis. These processes converge to exaggerate the reliability of forensic voice analysis. We complement our examination with plausibility ratings of a subset of excerpts. We claim that these biased representations have led to a situation where, even today, one of the main challenges faced by forensic voice specialists is to convince trial jurors, judges, lawyers, and police officers that forensic voice comparison can by no means give the sort of straightforward answers that fingerprints or DNA permit. Full article

The digital revolution has launched myriad new technologies in the field of art and cultural heritage law, including digital art, NFTs (non-fungible tokens), artificial intelligence (AI)-generated art, virtual reality and reality augmentation, online viewing rooms and auctions, holograms, immersive experiences, and more. As a $67.8 billion industry, the art market is a global driver of innovation, international collaboration, and national economies, given its cross-border transactions. However, given the extremely rapid development of these new technologies, regulators have struggled to keep pace and implement legal measures that are fit for purpose in this field. Limited oversight has resulted in several claims that have the potential to change the legal landscape. For instance, claims over the theft/misappropriation of NFTs and the related fraud and money laundering that may ensue, as well as a recent class action copyright infringement suit against the creators of a popular AI algorithm and infringement claims over immersive installation and light technologies, demonstrate how new ways of thinking are required to assess cases involving digital property (distinguished from other types of non-tangible property). Moreover, the US Supreme Court has issued a landmark ruling on fair use within the copyright context, which will be relied upon in the future to determine whether (and to what extent) the appropriation of existing copyrighted material is permitted. This includes both the digital use of physical artworks and the use of born-digital works. Although jurisprudential decisions are made on a case-by-case basis, factual patterns involving online media, digital art, and related technologies could serve as guidance for legislators and other decision-makers when considering what limits should be imposed on Web 3.0. This article will focus on recent US-based claims and regulations and dovetail with existing art market regulations in this jurisdiction (e.g., anti-money-laundering statutes) to determine their impact on new technologies, whether directly or indirectly. Finally, the article highlights ongoing trends and preoccupations to provide an overview of the shifting legal landscape. Full article

A high-performance Driver State Monitoring (DSM) application for the detection of driver drowsiness is presented in this paper. The popular Ensemble of Regression Trees (ERTs) machine learning method has been employed for the alignment of 68 facial landmarks. Open-source implementation of ERTs for facial shape alignment has been ported to different platforms and adapted for the acceleration of the frame processing speed using reconfigurable hardware. Reducing the frame processing latency saves time that can be used to apply frame-to-frame facial shape coherency rules. False face detection and false shape estimations can be ignored for higher robustness and accuracy in the operation of the DSM application without sacrificing the frame processing rate that can reach 65 frames per second. The sensitivity and precision in yawning recognition can reach 93% and 97%, respectively. The implementation of the employed DSM algorithm in reconfigurable hardware is challenging since the kernel arguments require large data transfers and the degree of data reuse in the computational kernel is low. Hence, unconventional hardware acceleration techniques have been employed that can also be useful for the acceleration of several other machine learning applications that require large data transfers to their kernels with low reusability. Full article

The diversity of patients pursuing facial aesthetic and facial gender-affirming surgery (FGAS) is increasing, yet there is a paucity of objective guidelines to facilitate surgical decision-making in patients of color. We conducted a quantitative analysis of black celebrities using standardized frontal photos of 21 female and 21 male celebrities. Celebrities were chosen from popular entertainment magazines and websites, including People Magazine, the Internet Movie Database (IMDb), Cosmopolitan, and Essence. For each celebrity, 100 facial landmarks were detected through a facial analysis artificial intelligence (AI) program. Black males had greater facial height, bizygomatic width, lower facial height, and bigonial width than females. However, the facial height to bigonial width ratio was similar between genders and approximated the golden ratio (1.618). Female faces demonstrated a greater mid-face height to total facial height proportion, and males had a greater lower facial height proportion. Females exhibited an upward-slanted medial brow and shorter total eyebrow length, nose height, and alar width. Forehead height above the lateral brow was greater in males, while central forehead height was similar to females. This is the first study that has utilized AI to provide ethnicity-specific facial morphometrics relevant to facial rejuvenation and FGAS in the black population. Full article

With a growing geriatric population estimated to triple by 2050, minimally invasive procedures that are image-guided are becoming both more popular and necessary for treating a variety of diseases. To lower the learning curve for new procedures, it is necessary to develop better guidance systems and methods to analyze procedure performance. Since fluoroscopy remains the primary mode of visualizations, the ability to perform catheter tracking from fluoroscopic images is an important part of this endeavor. This paper explores the use of deep learning to perform the landmark detection of a catheter from fluoroscopic images in 3D-printed heart models. We show that a two-stage deep-convolutional-neural-network-based model architecture can provide improved performance by initially locating a region of interest before determining the coordinates of the catheter tip within the image. This model has an average error of less than 2% of the image resolution and can be performed within 4 milliseconds, allowing for its potential use for real-time intraprocedural tracking. Coordinate regression models have the advantage of directly outputting values that can be used for quantitative tracking in future applications and are easier to create ground truth values (~50× faster), as compared to semantic segmentation models that require entire masks to be made. Therefore, we believe this work has better long-term potential to be used for a broader class of cardiac devices, catheters, and guidewires. Full article

The accurate localization of facial landmarks is essential for several tasks, including face recognition, head pose estimation, facial region extraction, and emotion detection. Although the number of required landmarks is task-specific, models are typically trained on all available landmarks in the datasets, limiting efficiency. Furthermore, model performance is strongly influenced by scale-dependent local appearance information around landmarks and the global shape information generated by them. To account for this, we propose a lightweight hybrid model for facial landmark detection designed specifically for pupil region extraction. Our design combines a convolutional neural network (CNN) with a Markov random field (MRF)-like process trained on only 17 carefully selected landmarks. The advantage of our model is the ability to run different image scales on the same convolutional layers, resulting in a significant reduction in model size. In addition, we employ an approximation of the MRF that is run on a subset of landmarks to validate the spatial consistency of the generated shape. This validation process is performed against a learned conditional distribution, expressing the location of one landmark relative to its neighbor. Experimental results on popular facial landmark localization datasets such as 300 w, WFLW, and HELEN demonstrate the accuracy of our proposed model. Furthermore, our model achieves state-of-the-art performance on a well-defined robustness metric. In conclusion, the results demonstrate the ability of our lightweight model to filter out spatially inconsistent predictions, even with significantly fewer training landmarks. Full article

Catheterization is a procedure used to diagnose and treat various cardiovascular diseases. Intracardiac echocardiography (ICE) is an emerging imaging modality that has gained popularity in these procedures due to its ability to provide high-resolution images of the heart and its surrounding structures in a minimally invasive manner. However, given its limited field of view, its orientation within the heart is difficult to judge simply from observing the acquired images. Therefore, ICE catheter tracking, which requires six degrees of freedom, would be useful to better guide interventionalists during a procedure. This work demonstrates a machine learning-based approach that has been trained to predict the roll angle of an ICE catheter using landmark scalar values extracted from bi-plane fluoroscopy images. The model consists of two fully connected deep neural networks that were trained on a dataset of bi-plane fluoroscopy images acquired from a 3D printed heart phantom. The results showed high accuracy in roll angle prediction, suggesting the ability to achieve 6 degrees of freedom tracking using bi-plane fluoroscopy that can be integrated into future navigation systems embedded into the c-arm, integrated within an AR/MR headset, or in other commercial navigation systems. Full article

In this paper, we present a non-rigid point cloud matching method based on an invariant structure for face deformation. Our work is guided by the realistic needs of 3D face reconstruction and re-topology, which critically need support for calculating the correspondence between deformable models. Our paper makes three main contributions: First, we propose an approach to normalize the global structure features of expressive faces using texture space properties, which decreases the variation magnitude of facial landmarks. Second, we make a modification to the traditional shape context descriptor to solve the problem of regional cross-mismatch. Third, we collect a dataset with various expressions. Ablation studies and comparative experiments were conducted to investigate the performance of the above work. In face deformable cases, our method achieved 99.89% accuracy on our homemade face dataset, showing superior performance over some other popular algorithms. In this way, it can help modelers to build digital humans more easily based on the estimated correspondence of facial landmarks, saving a lot of manpower and time. Full article

The image of a city represents the sum of beliefs, ideas, and impressions that people have of that city. Mostly, city images are assessed through direct or indirect interviews and cognitive mapping exercises. Such methods consume more time and effort and are limited to a small number of people. However, recently, people tend to use social media to express their thoughts and experiences of a place. Taking this into consideration, this paper attempts to explore city images through social media big data, considering Colombo, Sri Lanka, as the testbed. The aim of the study is to examine the image of a city through Lynchian elements—i.e., landmarks, paths, nodes, edges, and districts—by using community sentiments expressed and images posted on social media platforms. For that, this study conducted various analyses—i.e., descriptive, image processing, sentiment, popularity, and geo-coded social media analyses. The study findings revealed that: (a) the community sentiments toward the same landmarks, paths, nodes, edges, and districts change over time; (b) decisions related to locating landmarks, paths, nodes, edges, and districts have a significant impact on community cognition in perceiving cities; and (c) geo-coded social media data analytics is an invaluable approach to capture the image of a city. The study informs urban authorities in their placemaking efforts by introducing a novel methodological approach to capture an image of a city. Full article

With the rapid development of technology, unmanned aerial vehicles (UAVs) have become more popular and are applied in many areas. However, there are some environments where the Global Positioning System (GPS) is unavailable or has the problem of GPS signal outages, such as indoor and bridge inspections. Visual inertial odometry (VIO) is a popular research solution for non-GPS navigation. However, VIO has problems of scale errors and long-term drift. This study proposes a method to correct the position errors of VIO without the help of GPS information for vertical takeoff and landing (VTOL) UAVs. In the initial process, artificial landmarks are utilized to improve the positioning results of VIO by the known landmark information. The position of the UAV is estimated by VIO. Then, the accurate position is estimated by the extended Kalman filter (EKF) with the known landmark, which is used to obtain the scale correction using the least squares method. The Inertial Measurement Unit (IMU) data are used for integration in the time-update process. The EKF can be updated with two measurements. One is the visual odometry (VO) estimated directly by a landmark. The other is the VIO with scale correction. When the landmark is detected during takeoff phase, or the UAV is returning to the takeoff location during landing phase, the trajectory estimated by the landmark is used to update the scale correction. At the beginning of the experiments, preliminary verification was conducted on the ground. A self-developed UAV equipped with a visual–inertial sensor to collect data and a high-precision real time kinematic (RTK) to verify trajectory are applied to flight tests. The experimental results show that the method proposed in this research effectively solves the problems of scale and the long-term drift of VIO. Full article

Over the last decade, a driver’s distraction has gained popularity due to its increased significance and high impact on road accidents. Various factors, such as mood disorder, anxiety, nervousness, illness, loud music, and driver’s head rotation, contribute significantly to causing a distraction. Many solutions have been proposed to address this problem; however, various aspects of it are still unresolved. The study proposes novel geometric and spatial scale-invariant features under a boosting framework for detecting a driver’s distraction due to the driver’s head panning. These features are calculated using facial landmark detection algorithms, including the Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). The proposed approach is compared with six existing state-of-the-art approaches using four benchmark datasets, including DrivFace dataset, Boston University (BU) dataset, FT-UMT dataset, and Pointing’04 dataset. The proposed approach outperforms the existing approaches achieving an accuracy of 94.43%, 92.08%, 96.63%, and 83.25% on standard datasets. Full article

Skyscrapers are symbols of local landmarks, and their prevalence is increasing across the world owing to recent advances in architectural technology. In Korea, the Lotte World Tower, which is now the tallest skyscraper in Seoul, was constructed in 2017. In addition, it has an observatory deck called Seoul Sky, which is currently in operation. This study focuses on the design of Seoul AR, which is a mobile augmented reality (AR) tour application. Visitors can use Seoul AR when visiting the Seoul Sky Observatory, one of the representative landmarks of Seoul, and enjoy a 360° view of the entire landscape of Seoul in the observatory space. With Seoul AR, they can identify tourist attractions in Seoul with simple mission games. Users are also provided with information regarding the specific attraction they are viewing, as well as other information on transportation, popular restaurants, shopping places, etc., in order to increase the level of satisfaction of tourists visiting the Seoul Sky Observatory. The final design is revised through heuristic evaluation, and a study of users’ levels of satisfaction with Seoul AR is conducted through surveys completed by visitors to the Seoul Sky Observatory. Full article